Tal Arbel

Mila > About Mila > Team > Tal Arbel
Associate Academic Member
Tal Arbel
Professor, McGill University
Tal Arbel

My research goals are to develop new probabilistic machine learning frameworks in computer vision and in medical imaging, particularly in the context of neurology and neurosurgery. Recent work has focused on the development of probabilistic graphical models for pathology (lesion, tumour) detection and segmentation in large, multi-center patient images dataset as well as on modeling and conveying uncertainties in deep learning models. I have worked extensively on developing fast and efficient multi-modal image registration techniques for clinical interventions, such as image-guided neurosurgery. Recent work focuses on automatically identifying imaging biomarkers that predict disease progression in patients with Multiple Sclerosis as well as identifying potential responders to treatment. This includes developing spatio-temporal models for disease evolution which include clinical and imaging information in learning and inference.

Publications

2021-11

Estimating treatment effect for individuals with progressive multiple sclerosis using deep learning
Jean-Pierre R. Falet, Joshua Durso-Finley, Brennan Nichyporuk, Julien Schroeter, Francesca Bovis, Maria-Pia Sormani, Doina Precup, Tal Arbel and Douglas Lorne Arnold
medRxiv
(2021-11-01)
www.medrxiv.org

2021-09

Propagating Uncertainty Across Cascaded Medical Imaging Tasks For Improved Deep Learning Inference
Raghav Mehta, Thomas Christinck, Tanya Nair, Aurelie Bussy, Swapna Premasiri, Manuela Costantino, Mallar Chakravarty, Douglas L Arnold, Yarin Gal and Tal Arbel
IEEE Transactions on Medical Imaging
(2021-09-20)
ieeexplore.ieee.org

2021-08

Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation
Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Sotirios A. Tsaftaris, Douglas L. Arnold and Tal Arbel

2021-04

Common Limitations of Image Processing Metrics: A Picture Story
Annika Reinke, Matthias Eisenmann, Minu Dietlinde Tizabi, Carole H. Sudre, Tim Rädsch, Michela Antonelli, Tal Arbel, Spyridon Bakas, M. Jorge Cardoso, Veronika Cheplygina, Keyvan Farahani, Ben Glocker, Doreen Heckmann-Nötzel, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Jens Kleesiek, Tahsin M. Kurç, Michal Kozubek, Bennett A. Landman... (14 more)
arXiv: Computer Vision and Pattern Recognition
(2021-04-12)
ui.adsabs.harvard.eduPDF
Optimizing Operating Points for High Performance Lesion Detection and Segmentation Using Lesion Size Reweighting.
Brennan Nichyporuk, Justin Szeto, Douglas L. Arnold and Tal Arbel
Common limitations of performance metrics in biomedical image analysis
Annika Reinke, Matthias Eisenmann, Minu Dietlinde Tizabi, Carole H. Sudre, Tim Rädsch, Michela Antonelli, Tal Arbel, Spyridon Bakas, M. Jorge Cardoso, Veronika Cheplygina, Keyvan Farahani, Ben Glocker, Doreen Heckmann-Nötzel, Fabian Isensee, Pierre Jannin, Charles Kahn, Jens Kleesiek, Tahsin Kurc, Michal Kozubek, Bennett A. Landman... (15 more)
(venue unknown)
(2021-04-01)
openreview.netPDF

2021-03

Accounting for Variance in Machine Learning Benchmarks
Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Naz Sepah, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Dmitriy Serdyuk, Tal Arbel, Chris Pal, Gaël Varoquaux and Pascal Vincent
MLsys 2021 - 4th Conference on Machine Learning and Systems
(2021-03-15)
proceedings.mlsys.orgPDF[Also on arXiv preprint arXiv:2103.03098 (2021-03-01)]

2021-02

HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images
Saverio Vadacchino, Raghav Mehta, Nazanin Mohammadi Sepahvand, Brennan Nichyporuk, James J. Clark and Tal Arbel
Medical Imaging with Deep Learning
(2021-02-09)
dblp.uni-trier.dePDF
HAD-Net: A Hierarchical Adversarial Knowledge Distillation Network for Improved Enhanced Tumour Segmentation Without Post-Contrast Images
Saverio Vadacchino, Raghav Mehta, Nazanin Mohammadi Sepahvand, Brennan Nichyporuk, James J. Clark and Tal Arbel
Task dependent deep LDA pruning of neural networks
Qing Tian, Tal Arbel and James J. Clark

2020-10

Optimization over Random and Gradient Probabilistic Pixel Sampling for Fast, Robust Multi-Resolution Image Registration
Boris N. Oreshkin and Tal Arbel
arXiv preprint arXiv:2010.02505
(2020-10-02)
ui.adsabs.harvard.eduPDF
Uncertainty driven probabilistic voxel selection for image registration
Boris N. Oreshkin and Tal Arbel
arXiv preprint arXiv:2010.00988
(2020-10-02)
ui.adsabs.harvard.eduPDF

2020-09

Grow-Push-Prune: aligning deep discriminants for effective structural network compression
Qing Tian, Tal Arbel and James J. Clark
arXiv: Computer Vision and Pattern Recognition
(2020-09-29)
ui.adsabs.harvard.eduPDF
Deep discriminant analysis for task-dependent compact network search
Qing Tian, Tal Arbel and James J. Clark
arXiv preprint arXiv:2009.13716
(2020-09-29)
dblp.uni-trier.de

2020-08

Biomedical Image Analysis Challenges (BIAS) Reporting Guideline
Lena Maier-Hein, Annika Reinke, Michal Kozubek, Anne L. Martel, Tal Arbel, Matthias Eisenmann, Allan Hanbury, Pierre Jannin, Henning MĂĽller, Sinan Onogur, Julio Saez-Rodriguez, Bram van Ginneken, Annette Kopp-Schneider and Bennett A. Landman
(venue unknown)
(2020-08-31)
zenodo.orgPDF
BIAS: Transparent reporting of biomedical image analysis challenges.
Lena Maier-Hein, Annika Reinke, Michal Kozubek, Anne L. Martel, Tal Arbel, Matthias Eisenmann, Allan Hanbury, Pierre Jannin, Henning MĂĽller, Sinan Onogur, Julio Saez-Rodriguez, Bram van Ginneken, Annette Kopp-Schneider and Bennett A. Landman
Medical Image Analysis
(2020-08-21)
europepmc.org

2020-06

Medical Imaging with Deep Learning: MIDL 2020 - Short Paper Track.
Tal Arbel, Ismail Ben Ayed, Marleen de Bruijne, Maxime Descoteaux, Herve Lombaert and Chris Pal
arXiv preprint arXiv:2007.02319
(2020-06-29)
ui.adsabs.harvard.eduPDF

2020-05

Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis
Aaron Carass, Snehashis Roy, Adrian Gherman, Jacob C. Reinhold, Andrew Jesson, Tal Arbel, Oskar Maier, Heinz Handels, Mohsen Ghafoorian, Bram Platel, Ariel Birenbaum, Hayit Greenspan, Dzung L. Pham, Ciprian M. Crainiceanu, Peter A. Calabresi, Jerry L. Prince, William R. Gray Roncal, Russell T. Shinohara and Ipek Oguz
Scientific Reports
(2020-05-19)
europepmc.org

2020-04

CNN Detection of New and Enlarging Multiple Sclerosis Lesions from Longitudinal Mri Using Subtraction Images
Nazanin Mohammadi Sepahvand, Douglas L. Arnold and Tal Arbel
ISBI 2020
(2020-04-03)
doi.org
Deep LDA-pruned nets and their robustness
Qing Tian, Tal Arbel and James J. Clark
Les Cahiers du GERAD
(2020-04-01)
www.gerad.ca

2020-01

Exploring Bayesian Deep Learning Uncertainty Measures for Segmentation of New Lesions in Longitudinal MRIs
Nazanin Mohammadi Sepahvand, Raghav Mehta, Douglas Lorne Arnold, Doina Precup and Tal Arbel
(venue unknown)
(2020-01-25)
openreview.netPDF
Uncertainty Evaluation Metric for Brain Tumour Segmentation.
Raghav Mehta, Angelos Filos, Yarin Gal and Tal Arbel
Exploring uncertainty measures in deep networks for Multiple sclerosis lesion detection and segmentation.
Tanya Nair, Doina Precup, Douglas L. Arnold and Tal Arbel

2019-12

Author correction: Why rankings of biomedical image analysis competitions should be interpreted with care (Nature Communications, (2018), 9, 1, (5217), 10.1038/s41467-018-07619-7)
Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew P. Bradley, Aaron Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken, Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno März, Oskar Maier... (18 more)
Nature Communications
(2019-12-01)
research.tue.nl

2019-10

Saliency Based Deep Neural Network for Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI
Joshua Durso-Finley, Douglas L. Arnold and Tal Arbel
International MICCAI Brainlesion Workshop
(2019-10-17)
doi.org
Improving Pathological Structure Segmentation via Transfer Learning Across Diseases
Barleen Kaur, Paul Lemaître, Raghav Mehta, Nazanin Mohammadi Sepahvand, Doina Precup, Douglas L. Arnold and Tal Arbel
DART/MIL3ID@MICCAI
(2019-10-13)
link.springer.com
BIAS: Transparent reporting of biomedical image analysis challenges
Lena Maier-Hein, Annika Reinke, Michal Kozubek, Anne L. Martel, Tal Arbel, Matthias Eisenmann, Allan Hanbuary, Pierre Jannin, Henning MĂĽller, Sinan Onogur, Julio Saez-Rodriguez, Bram van Ginneken, Annette Kopp-Schneider and Bennett Landman
arXiv preprint arXiv:1910.04071
(2019-10-09)
arxiv.orgPDF

2019-05

Stroke Lesion Segmentation in FLAIR MRI Datasets Using Customized Markov Random Fields.
Nagesh K. Subbanna, Deepthi Rajashekar, Bastian Cheng, Götz Thomalla, Jens Fiehler, Tal Arbel and Nils D. Forkert
Frontiers in Neurology
(2019-05-24)
europepmc.org
Prediction of Disease Progression in Multiple Sclerosis Patients using Deep Learning Analysis of MRI Data
Adrian Tousignant, Paul Lemaître, Doina Precup, Douglas L. Arnold and Tal Arbel
International Conference on Medical Imaging with Deep Learning
(2019-05-24)
proceedings.mlr.pressPDF

2019-01

Why rankings of biomedical image analysis competitions should be interpreted with care (vol 9, 5217, 2018)
Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew P. Bradley, Aaron Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken, Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno Maerz, Oskar Maier... (18 more)
Nature Communications
(2019-01-30)
eprints.whiterose.ac.uk
Author Correction: Why rankings of biomedical image analysis competitions should be interpreted with care.
Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew P. Bradley, Aaron Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken, Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno März, Oskar Maier... (18 more)
Nature Communications
(2019-01-30)
europepmc.org
Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference.
Raghav Mehta, Thomas Christinck, Tanya Nair, Paul Lemaître, Douglas L. Arnold and Tal Arbel
UNSURE/CLIP@MICCAI
(2019-01-01)
doi.org

2018-12

Prediction of Progression in Multiple Sclerosis Patients
Adrian Tousignant, Paul Lemaître, Doina Precup, Douglas Arnold and Tal Arbel
International Conference on Medical Imaging with Deep Learning -- Full Paper Track
(2018-12-13)
openreview.netPDF
Why rankings of biomedical image analysis competitions should be interpreted with care
Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew Bradley, Aaron Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken, Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno März, Oskar Maier... (18 more)
Nature Communications
(2018-12-06)
econpapers.repec.orgPDF

2018-11

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipkova, John Freymann, Justin Kirby, Michel Bilello, Hassan Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler... (403 more)
Unknown Journal
(2018-11-05)
hal.inria.frPDF
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipkova, John Freymann, Justin Kirby, Michel Bilello, Hassan Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler... (403 more)
arXiv: Computer Vision and Pattern Recognition
(2018-11-05)
spiral.imperial.ac.ukPDF

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